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Synthesize High-Quality Multi-Contrast Magnetic Resonance Imaging From Multi-Echo Acquisition Using Multi-Task Deep Generative Model., , , , , , , , , and . IEEE Trans. Medical Imaging, 39 (10): 3089-3099 (2020)Random Bundle: Brain Metastases Segmentation Ensembling through Annotation Randomization., , , , , and . CoRR, (2020)Brain Metastasis Segmentation Network Trained with Robustness to Annotations with Multiple False Negatives., , , , , and . CoRR, (2020)Beyond the Hype: Assessing the Performance, Trustworthiness, and Clinical Suitability of GPT3.5., , and . CoRR, (2023)Handling Missing MRI Input Data in Deep Learning Segmentation of Brain Metastases: A Multi-Center Study., , , , , , , , , and 2 other author(s). CoRR, (2019)Exploring the performance and explainability of fine-tuned BERT models for neuroradiology protocol assignment., , , , , and . BMC Medical Informatics Decis. Mak., 24 (1): 40 (December 2024)Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study., , , , , , , , , and 2 other author(s). npj Digit. Medicine, (2021)2.5D and 3D segmentation of brain metastases with deep learning on multinational MRI data., , , , , , , , , and 3 other author(s). Frontiers Neuroinformatics, (August 2022)